Wireless sensor network is a totally new information acquiring and processing technology, and has a wide application prospect in industry, military, environment, healthcare and other fields. However, as a distributed computing platform, node resources such as Central Processing Unit (referred to as CPU) speed, storage space, power and bandwidth are very limited, and the working environment of the wireless sensor network is unpredictable, a variety of external interference factors (such as temperature, vibration, electromagnetic field, etc.) are likely to cause failures such as RF conflicts, clock asynchrony, battery depletion, signal loss, software errors, and so on occurred in the network, which greatly reduce the reliability of sensor nodes, weaken or fail intended functions in the wireless sensor network. Various abnormal situations in the network will be diagnosed in a timely manner, searching for reasonable tolerance control solutions that guide the normal operation of the network, which has great significance in improving the reliability and robustness of the wireless sensor network.
Currently, the structure of wireless sensor network is more and more complicated, its function becomes perfect, and the degree of automation becomes higher and higher. How to prolong its life as far as possible is a relatively popular topic in recent years. The life of the wireless sensor network is mainly decided by the life of the node. However, the wireless sensor network often runs in an unattended, inaccessible by humans, harsh or even dangerous, remote environment, due to many unavoidable factors, the nodes have a variety of failures, which reduces or loses the intended functions of the wireless sensor network, and even causes serious damage and even paralysis of the entire network.
Biologists used the wireless sensor network in 2002 to finely observe the habits of petrels on a certain island. 30 sensor nodes were deployed on the island, and after the network ran for 20 days, more than half of the nodes failed completely, obviously, the failure rate of the nodes is very high. Failure rate of sensing components (modules) of the humidity sensor nodes and the nodes within the network is very high. In view of this, the design of the wireless sensor network must take failure diagnosis of the nodes, especially failure diagnosis of the node sensor components, into consideration.
The current wireless network diagnostics technology is mainly inserting additional control information data packets into the network, depending on these data packets, the network state is detected in real time, and this method uses the active inquiry mode, generally, particular nodes in the network send the control information data packets to each node, and after the nodes receive the control information packets, they feed back their own state to the particular node, after the particular node determines the current network state according to the received feedback, therefore, this active inquiry mode brings relatively great communication expenses to the network. Especially, in the case that the network state changes frequently, these additional communication overheads increase network traffic load.
So far, there is no effective solution for the problem of relatively heavy network burden caused by the method of determining the network state through the active inquiry mode in the related art.